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Logo: Institut für Verteilte Systeme - Fachgebiet Wissensbasierte Systeme (KBS)
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Logo: Institut für Verteilte Systeme - Fachgebiet Wissensbasierte Systeme (KBS)
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Web Science

Important Infos

Please select a date for your oral exam using the link below:


Location: KBS, Appelstr. 4, 2nd floor, Prof. Nejdl's office (please ring the bell to enter the floor and wait in the waiting room in the middle of the hall). 


Course start: 25.04.2017, 15:00-16:30, Multimedia-Hörsaal (3703 - 023)

Teaching Team:

  • Responsible Professor: Prof. Dr. techn. Wolfgang Nejdl
  • Assistant: Andrea Ceroni  (Home Page)
  • NOTE: Please put "[WebScienceCourse]" into the subject line when writing an email


  • Lecture: Tuesdays 15:00 - 16:30
  • Room: Multimedia-Hörsaal (3703 - 023), Appelstraße 4, 30167 Hannover
  • Live - Transmition:  https://webconf.vc.dfn.de/websciencecourse (please ask Andrea for the password to access this virtual room)

Oral Exam

The oral exam consists of two parts:

  1. Detailed questions on the papers presented by the student during the course. The presentation of the papers is compulsory!
  2. More general questions on other papers of the same topicand some on other topics. As a guideline you should be able to answer the following questions:

    • What is the problem addressed in the paper?
    • How does the solution look like?
    • How is it evaluated?

Topics for Student Paper Presentation

Below are the topics of Web Science that will be addressed in the course. Each student will have to pick two papers that she/he will present to the other students in the second part of the course. Details about how to subscribe will follow.


  • Here we collected hints helping you to prepare a good presentation.
  • You are highly encouraged to use the provided slide template for your presentation: powerpoint latex


Send a mail to Andrea with the following details:

  • At least 2 papers that you wish to present.
  • Any time period (if exists) during the semester lecture period in which you absolutely cannot present.
  • Any time period (if exists) when you would preferably present.


We will try to take the following criteria into account when assigning papers to students:

  • Papers will be assigned to students as soon as possible according to the first come first served policy.
  • The exact presentation date will be fixed as soon as 2 papers about the same topic has been assigned.
  • Presentations about the same topic should take place the same day.
  • A similar number of papers per topic should be presented (as far as possible).
  • Each topic should have at least one paper presented.

Available Topic Papers

Below are the papers to be chosen and presented, grouped by topic.


1. Event Detection

  • Foley, John and Bendersky, Michael and Josifovski, Vanja. Learning to Extract Local Events from the Web. SIGIR '15.[PDF]
  • Sunandan Chakraborty, Ashwin Venkataraman, Srikanth Jagabathula. Predicting Socio-Economic Indicators using News Events. KDD ’16. [PDF]
  • Jatowt, Adam and Antoine, Emilien and Kawai, Yukiko and Akiyama, Toyokazu. Mapping Temporal Horizons: Analysis of Collective Future and Past related Attention in Twitter. WWW ’15. [PDF]
  • Zhao, Liang and Sun, Qian and Ye, Jieping and Chen, Feng and Lu, Chang-Tien and Ramakrishnan, Naren. Multi-Task Learning for Spatio-Temporal Event Forecasting. KDD '15. [PDF]


2. Fairness and Transparency for Big Data Analysis

  • [Selected by Muhammad Jawad] Tien T. Nguyen, Pik-Mai Hui, F. Maxwell Harper, Loren Terveen, Joseph A. Konstan. Exploring the Filter Bubble: The Effect of Using Recommender Systems on Content Diversity. WWW '14. [PDF]
  • [Selected by Muhammad Jawad] Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez Rodriguez, Krishna P. Gummadi. Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment. WWW '17. [PDF]
  • [Selected by Yuqiao Bai] Tolga Bolukbasi, Kai-Wei Chang, James Zou, Venkatesh Saligrama, Adam Kalai. Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings. NIPS '16. [PDF]
  • [Selected by Yuqiao Bai] Aylin Caliskan-Islam, Joanna J. Bryson, Arvind Narayanan. Semantics derived automatically from language corpora necessarily contain human biases. 2016. [PDF]


3. Mining the Social Web

  • [Selected by Shaheer Asghar] Paul Laufer, Claudia Wagner, Fabian Flöck, Markus Strohmeier. Mining cross-cultural relations from Wikipedia-A study of 31 European food cultures. WebSci '15. [PDF]
  • [Selected by Eric Wete] Conover, Michael, et al. Political Polarization on Twitter. ICWSM '11. [PDF]
  • [Selected by Eric Wete] Weber, Ingmar, Venkata Rama Kiran Garimella, and Asmelash Teka. Political hashtag trends. ECIR '13. [PDF]
  • [Selected by Shaheer Asghar] Kocabey, Enes, Mustafa Camurcu, Ferda Ofli, Yusuf Aytar, Javier Marin, Antonio Torralba, and Ingmar Weber. Face-to-bmi: Using computer vision to infer body mass index on social media. CoRR '17. [PDF]


4. Crowdsourcing

  • [Selected by Chenyu He] Difallah, Djellel Eddine, et al. The dynamics of micro-task crowdsourcing: The case of amazon mturk. WWW '15. [PDF]
  • [Selected by Chenyu He] Raykar, Vikas C., et al. Learning from crowds. JMLR '10. [PDF]
  • Kazai, Gabriella. In search of quality in crowdsourcing for search engine evaluation. ECIR '11. [PDF]
  • Bernstein, Michael S., et al. Soylent: a word processor with a crowd inside. UIST '10. [PDF]


5. Accessing Web Archives

  • Jure Leskovec, Jon Kleinberg, and Christos Faloutsos. Graphs over time: densification laws, shrinking diameters and possible explanations. KDD '05 [PDF]
  • Marijn Koolen and Jaap Kamps. The Importance of Anchor Text for Ad Hoc Search Revisited. SIGIR '00 [PDF]
  • Avishek Anand, Srikanta Bedathur, Klaus Berberich, and Ralf Schenkel. Index Maintenance for Time-Travel Text Search. SIGIR '12 [PDF]
  • Liudmila Ostroumova Prokhorenkova et al. Publication Date Prediction through Reverse Engineering of the Web. WSDM '16 [PDF]


6. Semantic Text Mining

  • [Selected by Markus Krömker] Vlad Niculae, Joonsuk Park, Claire Cardie. Argument Mining with Structured SVMs and RNNs. ACL '17. [PDF]
  • [Selected by Han Tran] David Tsurel , Dan Pelleg, Ido Guy, Dafna Shahaf. Fun Facts: Automatic Trivia Fact Extraction from Wikipedia. WSDM '17. [PDF]
  • [Selected by Han Tran] Abdalghani Abujaba, Mohamed Yahya, Mirek Riedewald, Gerhard Weikum. Automated Template Generation for Question Answering over Knowledge Graphs. WWW '17. [PDF]
  • [Selected by Markus Krömker] William L. Hamilton, Jure Leskovec, Dan Jurafsky. Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change. CoRR '16. [PDF]


7. Multilingual Information Access

  • David Mimno, Hanna M. Wallach, Jason Naradowsky, David A. Smith, Andrew McCallum. Polylingual topic models. MNLP '09. [PDF]
  • Camacho-Collados, José, Mohammad Taher Pilehvar, and Roberto Navigli. A Unified Multilingual Semantic Representation of Concepts. ACL '15 [PDF]
  • Vulić, Ivan, and Marie-Francine Moens. Monolingual and cross-lingual information retrieval models based on (bilingual) word embeddings. SIGIR '15. [PDF]
  • Hecht, Brent, and Darren Gergle. The tower of Babel meets web 2.0: user-generated content and its applications in a multilingual context. SIGCHI '10. [PDF]


8. SaR-Web: Search as research practices on the web - cross-language engine results analysis

  • Rogers R., Jansen F., Stevenson M. and Weltevrede E. Mapping Democracy. Global Informaton Society Watch, Association for Progressive Communications and Hivos, 2009. [PDF]
  • Davide Taibi, Richard Rogers, Ivana Marenzi, Wolfgang Nejdl, Asim Ijaz, Giovanni Fulantelli. Search as research practices on the web: The SaR-Web platform for cross-language engine results analysis. WebSci '16. [PDF]
  • [Selected by Sun Feier] Stefano Parmesan, Ugo Scaiella, Michele Barbera, and Tatiana Tarasova. Dandelion: from raw data to dataGEMs for developers. ISWC-DEV '14. [PDF]
  • [Selected by Sun Feier] M. A. Hearst and D. Rosner. Tag Clouds: Data Analysis or Social Signaller?. HICSS '08. [PDF]
  • [Selected by Fourat Belhaj Rhouma] Dat Ba Nguyen, Johannes Hoffart, Martin Theobald, Gerhard Weikum. AIDA-light: High-Throughput Named-Entity Disambiguation. LDOW '14. [PDF]
  • [Selected by Fourat Belhaj Rhouma] Chen, Jiangping and Bao, Yu. Cross-language search: The case of Google Language Tools. First Monday '09. [PDF]
  • Anat Ben-David and Hugo Huurdeman. 2014. Web Archive Search as Research: Methodological and Theoretical Implications. Alexandria 25.1: 93–111. [PDF]

Detailed Schedule

25.04.2017 - Lecture

  • Introduction to Web Science (Andrea Ceroni) - Slides
  • Event Detection (Andrea Ceroni) - Slides PPT


02.05.2017 - Lecture

  • Fairness and Transparency for Big Data Analysis (Prof. Dr. Wolfgang Nejdl) - Slides


09.05.2017 - Lecture

  • Mining the Social Web (Asmelash Teka) - Slides
  • Crowdsourcing (Markus Rokicki) - Slides


16.05.2017 - Lecture

  • Accessing Web Archives (Helge Holzmann) - Slides
  • Semantic Text Mining (Besnik Fetahu) - Slides


23.05.2017 - Lecture

  • Multilingual Information Access (Simon Gottschalk) - Slides
  • SaR-Web: Search as research practices on the web - cross-language engine results analysis (Dr. Ivana Marenzi, Qazi Asim Ijaz Ahmad) - Slides


Topics and papers selected by students:


Shaheer AsgharMining the Social Web1st, 4th30.05pptx
Eric WeteMining the Social Web2nd, 3rd13.06pdf
Fourat Belhaj RhoumaSearch as Research5th, 6th13.06pdf
Chenyu HeCrowdsourcing1st, 2nd20.06pptx
Zhongda ZhaiCrowdsourcing3rd, 4th20.06not presented
Han TranSemantic Text Mining2nd, 3rd


Markus KrömkerSemantic Text Mining1st, 4th


Muhammad JawadFairness and Transparency1st, 2nd04.07pdf
Yuqiao BaiFairness and Transparency3rd, 4th04.07pdf
Sun FeierSearch as Research3rd, 4th11.07ppt


Final Oral Exam